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Possible contribution of quantum-like correlations to the placebo effect: consequences on blind trials

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Background. Factors that participate in the biological changes associated with a placebo are not completely understood. Natural evolution, mean regression, concomitant procedures and other non specific effects are well-known factors that contribute to the “placebo effect”. In this article, we suggest that quantum-like correlations predicted by a probabilistic modeling could also play a role. Results. An elementary experiment in biology or medicine comparing the biological changes associated with two placebos is modeled. The originality of this modeling is that experimenters, biological system and their interactions are described together from the standpoint of a participant who is uninvolved in the measurement process. Moreover, the small random probability fluctuations of a “real” experiment are also taken into account. If both placebos are inert (with only different labels), common sense suggests that the biological changes associated with the two placebos should be comparable. However, the consequence of this modeling is the possibility for two placebos to be associated with different outcomes due to the emergence of quantum-like correlations. Conclusion. The association of two placebos with different outcomes is counterintuitive and this modeling could give a framework for some unexplained observations where mere placebos are compared (in some alternative medicines for example). This hypothesis can be tested in blind trials by comparing local vs. remote assessment of correlations.
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... In order to mitigate and possibly detect the phenomena mimicking a placebo effect (59), one proposed methodological approach is to include a "no treatment" arm, in which "no treatment" is administered, as part of a "three-arms trial" (60,61), comprising a real intervention, a sham control, and the additional no-intervention control group (42,62,63). . Although this is seldomly used (64)(65)(66), including a "no-treatment" arm could not only detect the causal effect of the placebo (39,(67)(68)(69)(70)(71)(72) but also allow for estimating a more precise effect of the treatment and placebo (54,65,66). Three distinct types of no-treatment groups have been used: 1) Non-manual, non-specific control group: a 'hands-off' group in which participants are exposed to all aspects of the research paradigm (i.e., setting, patient-clinician contact) without being touched (40), thus preserving all non-manual, non-specific elements of placebo. ...
... In order to mitigate and possibly detect the phenomena mimicking a placebo effect (59), one proposed methodological approach is to include a "no treatment" arm, in which "no treatment" is administered, as part of a "three-arms trial" (60,61), comprising a real intervention, a sham control, and the additional no-intervention control group (42,62,63). . Although this is seldomly used (64)(65)(66), including a "no-treatment" arm could not only detect the causal effect of the placebo (39,(67)(68)(69)(70)(71)(72) but also allow for estimating a more precise effect of the treatment and placebo (54,65,66). Three distinct types of no-treatment groups have been used: 1) Non-manual, non-specific control group: a 'hands-off' group in which participants are exposed to all aspects of the research paradigm (i.e., setting, patient-clinician contact) without being touched (40), thus preserving all non-manual, non-specific elements of placebo. ...
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Randomised placebo-controlled trials are implemented to determine whether a particular therapy is superior to placebo and can thus be considered, effective. However, adopting the standard RCT design in contexts other than pharmacological trials, such as manual therapy, may result in systematic biases. These biases may occur due to: the impossibility of traditional “double-blinding” in manual therapy trials; insufficient pre-training of operators delivering the treatment and/or sham therapy; biased recruitment of study participants; the problematic use of subjective and/or objective outcomes; and finally, the presence of phenomena mimicking placebo effects. From the perspective of placebo studies, the purpose of this paper is to discuss and make appropriate recommendations to address these five issues in manual therapy research.
... It is worth noting that the placebo effect is considered more relevant in non-pharmacological treatments [20,21] including complementary alternative medicines (CAMs) [20,22]. It depends on several conditions, including the significant role of interpersonal touch [9], the multiplicity of treatment sessions [23], and the optimisation of the patient-physician relationship . ...
... Page 12 of 14 Giandomenico et al. BMC Medical Research Methodology (2022) 22:219 These Terms are supplementary and will apply in addition to any applicable website terms and conditions, a relevant site licence or a personal subscription. These Terms will prevail over any conflict or ambiguity with regards to the relevant terms, a site licence or a personal subscription (to the extent of the conflict or ambiguity only). ...
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Background To measure the specific effectiveness of a given treatment in a randomised controlled trial, the intervention and control groups have to be similar in all factors not distinctive to the experimental treatment. The similarity of these non-specific factors can be defined as an equality assumption. The purpose of this review was to evaluate the equality assumptions in manual therapy trials. Methods Relevant studies were identified through the following databases: EMBASE, MEDLINE, SCOPUS, WEB OF SCIENCE, Scholar Google, clinicaltrial.gov, the Cochrane Library, chiloras/MANTIS, PubMed Europe, Allied and Complementary Medicine (AMED), Physiotherapy Evidence Database (PEDro) and Sciencedirect. Studies investigating the effect of any manual intervention compared to at least one type of manual control were included. Data extraction and qualitative assessment were carried out independently by four reviewers, and the summary of results was reported following the PRISMA statement. Result Out of 108,903 retrieved studies, 311, enrolling a total of 17,308 patients, were included and divided into eight manual therapy trials categories. Equality assumption elements were grouped in three macro areas: patient-related, context-related and practitioner-related items. Results showed good quality in the reporting of context-related equality assumption items, potentially because largely included in pre-existent guidelines. There was a general lack of attention to the patient- and practitioner-related equality assumption items. Conclusion Our results showed that the similarity between experimental and sham interventions is limited, affecting, therefore, the strength of the evidence. Based on the results, methodological aspects for planning future trials were discussed and recommendations to control for equality assumption were provided.
... A new approach considering not only the "biological systems" (patients), but also the various "experimenters" and participants (physicians, patients, statisticians, etc) could be fruitful. Similarly, studies on placebo effect could also benefit from this original perspective if the "meaning" of the medicines -for both patients and physicians -is also considered [39,40]. ...
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Background: Benveniste’s biology experiments suggested the existence of molecular-like effects without molecules (“memory of water”). In this article, it is proposed that these disputed experiments could have been the consequence of a previously unnoticed and non-conventional experimenter effect. Methods: A probabilistic modelling is built in order to describe an elementary laboratory experiment. A biological system is modelled with two possible states (“resting” and “activated”) and exposed to two experimental conditions labelled “control” and “test”, but both biologically inactive. The modelling takes into account not only the biological system, but also the experimenters. In addition, an outsider standpoint is adopted to describe the experimental situation. Results: A classical approach suggests that, after experiment completion, the “control” and “test” labels of biologically-inactive conditions should be both associated with “resting” state (i.e. no significant relationship between labels and system states). However, if the fluctuations of the biological system are also considered, a quantum-like relationship emerges and connects labels and system states (analogous to a biological “effect” without molecules). Conclusions: No hypotheses about water properties or other exotic explanations are needed to describe Benveniste’s experiments, including their unusual features. This modelling could be extended to other experimental situations in biology, medicine and psychology.
... Alternative medicines such as homeopathy or placebo effect are examples where this model could be applied. 32 As depicted in this article, the structuration of the observer's mind by classical conditioning could organize the observations and measurements. In such a situation, the experimenters are trapped into a circular process: they describe what they contribute to construct and they construct what contributes to their description. ...
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Full-text available
The “memory of water” experiments suggested the existence of molecular-like effects without molecules. Although no convincing evidence of modifications of water – specific of biologically-active molecules – has been reported up to now, consistent changes of biological systems were nevertheless recorded. We propose an alternate explanation based on classical conditioning of the experimenter. Using a probabilistic model, we describe not only the biological system, but also the experimenter engaged in an elementary dose-response experiment. We assume that during conventional experiments involving genuine biologically-active molecules, the experimenter is involuntarily conditioned to expect a pattern, namely a relationship between descriptions (or “labels”) of experimental conditions and corresponding biological system states. The model predicts that the conditioned experimenter could continue to record the learned pattern even in the absence of the initial cause, namely the biologically-active molecules. The phenomenon is self-sustained because the observation of the expected pattern reinforces the initial conditioning. A necessary requirement is the use of a system submitted to random fluctuations with autocorrelated successive states (no forced return to the initial position). The relationship recorded by the conditioned experimenter is, however, not causal in this model because blind experiments with an “outside” supervisor lead to a loss of correlations (i.e., system states randomly associated to “labels”). In conclusion, this psychophysical model allows explaining the results of “memory of water” experiments without referring to water or another local cause. It could be extended to other scientific fields in biology, medicine and psychology when suspecting an experimenter effect.
... A new approach considering not only the "biological systems" (patients), but also the various "experimenters" and participants (physicians, patients, statisticians, etc.) could be fruitful. Similarly, studies on the placebo effect could also benefit from this original perspective if the "meaning" of the medicines-for both patients and physicians-is also considered [43,44]. ...
Article
Full-text available
Background: Benveniste's biology experiments suggested the existence of molecular-like effects without molecules ("memory of water"). In this article, it is proposed that these disputed experiments could have been the consequence of a previously unnoticed and non-conventional experimenter effect.Methods:A probabilistic modelling is built in order to describe an elementary laboratory experiment. A biological system is modelled with two possible states ("resting" and "activated") and exposed to two experimental conditions labelled "control" and "test", but both are biologically inactive. The modelling takes into account not only the biological system, but also the experimenters. In addition, an outsider standpoint is adopted to describe the experimental situation.Results:A classical approach suggests that, after experiment completion, the "control" and "test" labels of biologically-inactive conditions should both be associated with the "resting" state (i.e., no significant relationship between labels and system states). However, if the fluctuations of the biological system are also considered, a quantum-like relationship emerges and connects labels and system states (analogous to a biological "effect" without molecules).Conclusions:No hypotheses about water properties or other exotic explanations are needed to describe Benveniste's experiments, including their unusual features. This modelling could be extended to other experimental situations in biology, medicine, and psychology.
... A new approach considering not only the "biological systems" (patients), but also the various "experimenters" and participants (physicians, patients, statisticians, etc) could be fruitful. Similarly, studies on placebo effect could also benefit from this original perspective if the "meaning" of the medicines -for both patients and physicians -is also considered [13,14]. ...
Preprint
Full-text available
Background. In experimental sciences, conception of an experiment and record of the outcomes must be strictly separated. Although many possible pitfalls have been described, particularly in biological sciences, one cannot exclude unknown loopholes. Methods. A simple probabilistic modeling is constructed in order to describe experimenters testing the hypothesis of a relationship between some experimental conditions (supposed causes) and states of a biological system (observed effects). The modeling rests on two preliminary remarks. First, after assessment of a relationship, the outcome is not a property of the system alone, but is a property of the experimenters and the system taken as a whole. Second, as a consequence, the outcome does not preexist to measurement. Results. A biological system with two possible states ("resting" and "activated") exposed to two control conditions distinguished only by their "labels" is modeled. A classical approach suggests that the two control conditions are both associated with the "resting" state (i.e. no relationship). Nevertheless, if the fluctuations of the system are considered, the hypothesis of a significant relationship between "labels" and system states is confirmed. In contrast, if the outcomes are not globally recognized as a relationship, but remains unconnected by the experimenters, no significant relationship emerges. Conclusion. This probabilistic modeling suggests that, despite precautions, the strict separation of biological systems and experimenters is an ideal not necessarily achieved when the hypothesis of a relationship is tested. The consequences could be wrong conclusions about causal relationships. Specific blind procedures are proposed to prevent unwanted correlations involving the experimenters.
... A new approach considering not only the "biological systems" (patients), but also the various "experimenters" and participants (physicians, patients, statisticians, etc) could be fruitful. Similarly, studies on placebo effect could also benefit from this original perspective if the "meaning" of the medicines -for both patients and physicians -is also considered [13,14]. ...
Preprint
Background. In experimental sciences, conception of an experiment and record of the outcomes must be strictly separated. Although many possible pitfalls have been described, particularly in biological sciences, one cannot exclude unknown loopholes. Methods. A simple probabilistic modeling is constructed in order to describe experimenters testing the hypothesis of a relationship between some experimental conditions (supposed causes) and states of a biological system (observed effects). The modeling rests on two preliminary remarks. First, after assessment of a relationship, the outcome is not a property of the system alone, but is a property of the experimenters and the system taken as a whole. Second, as a consequence, the outcome does not preexist to measurement. Results. A biological system with two possible states (“resting” and “activated”) exposed to two control conditions distinguished only by their “labels” is modeled. A classical approach suggests that the two control conditions are both associated with the “resting” state (i.e. no relationship). Nevertheless, if the fluctuations of the system are considered, the hypothesis of a significant relationship between “labels” and system states is confirmed. In contrast, if the outcomes are not globally recognized as a relationship, but remains unconnected by the experimenters, no significant relationship emerges. Conclusion. This probabilistic modeling suggests that, despite precautions, the strict separation of biological systems and experimenters is an ideal not necessarily achieved when the hypothesis of a relationship is tested. The consequences could be wrong conclusions about causal relationships. Specific blind procedures are proposed to prevent unwanted correlations involving the experimenters.
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